R Engineer

About the Role

As a remote, hourly paid R Engineer, you will review AI-generated responses and generate high-quality R and data-analysis-focused content, evaluating the reasoning quality and step-by-step problem-solving behind each solution. You will assess solutions for accuracy, clarity, and adherence to the prompt; identify errors in statistical methodology or data-wrangling workflows; fact-check analytical results; write expert-level explanations and model solutions that demonstrate correct use of R; and rate and compare multiple AI responses based on correctness and reasoning quality. This contract role is with SME Careers, an AI Data Services company and subsidiary of SuperAnnotate.

Additional Information

• There is no immediate project for this role; if qualified, you will be among the first experts contacted when relevant opportunities arise.
• This engagement provides access to future projects through the expert network.

Key Responsibilities

• Review and evaluate AI-generated R code and data-analysis outputs for accuracy, clarity, and adherence to prompts.
• Identify errors in statistical methodology and data-wrangling workflows and fact-check analytical results.
• Write expert-level explanations and model solutions that demonstrate correct use of R, including step-by-step reasoning.
• Develop detailed prompts and responses to guide AI learning across various topics.
• Evaluate, rank, and compare multiple AI responses to improve model accuracy, fluency, and contextual relevance.
• Test AI models for potential inaccuracies or biases and validate reliability across use cases.

Qualifications

• 2+ years of hands-on experience using R for data analysis, statistics, or data science work.
• Strong proficiency in R programming, including data wrangling, functional programming patterns, and writing reusable functions or packages.
• Solid grounding in applied statistics (regression, inference, model validation) with practical experience implementing methods in R.
• Experience building end-to-end analyses in R that include data cleaning, exploratory analysis, modeling, and visualization.
• Familiarity with common R ecosystems such as tidyverse, data.table, and ggplot2.
• Professional experience in a data-focused role such as data scientist, statistician, or quantitative analyst.
• Minimum Bachelor’s degree in Statistics, Mathematics, Computer Science, or a closely related quantitative field.
• Significant experience using large language models (LLMs) to assist with coding, analysis design, and code review in R.
• Excellent English writing skills with the ability to document analyses and explain complex statistical ideas clearly to non-experts; minimum C1 English proficiency required.
• Previous experience with AI data training or model evaluation is strongly preferred.